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Design Considerations for Spatial Decision Support Ontologies
Karen Kemp, The Kohala CenterRobert Raskin, Jet Propulsion Laboratory
Naicong Li, University of Redlands
AAG 2009, Las Vegas, NevadaMarch 22 – 27, 2009
Design considerations for SDS ontologies
About the project:
• Part of the Spatial Decision Support Knowledge Portal project
• Initiated by the Redlands Institute, University of Redlands (fall 2007)
• Collaborative workshops on SDS ontologies held at The Redlands Institute (Feb 2008, May 2008)
• Establishment of the SDS Consortium (May 2008)• Portal development at The Redlands Institute• Several consortium internal release so far• Plan to open to public in April 2009
Design considerations for SDS ontologies
Outline
• The need for SDS ontologies• Intended users• Scope and coverage• Development process• Choice of classification scheme• Degree of formalization• Treatment of natural language• Modular design and Potential interface with other
ontologies• Advantages of ontology-based Knowledge Portal• Conclusion and future work
Design considerations for SDS ontologies
Definition of Spatial Decision Support (SDS)
Spatial decision support is the computational or informational assistance for making better informed decisions about problems with a geographic or spatial component. This support assists with the development, evaluation and selection of proper policies, plans, scenarios, projects, interventions, or solution strategies.
SDS Consortium, based on http://geoanalytics.net/VisA-SDS-2006/
Design considerations for SDS ontologies
Intended users
• People facing spatial decision problems - decision makers, practitioners, etc.
• University researchers and students
Usage:
• Find resources for spatial decision support• Learn about spatial decision support
Design considerations for SDS ontologies
The need for SDS ontologies
• To formally represent the body of knowledge in the field of SDS
• To organize the Information about SDS resources
• To promote semantic clarity of commonly used terms within a user community, in the area of spatial decision making
Design considerations for SDS ontologies
The need for SDS ontologies
• To facilitate the development of modular, re-usable, interoperable tools/services
• To facilitate the evaluation of existing spatial decision support systems and tools in terms of their functionality and interoperability
The need for SDS ontologies
Design considerations for SDS ontologies
Scope and coverage
• The body of knowledge is vast
• Focus:• Decision problem types• Decision context• Decision process (phases and steps)• Methods and techniques• SDSS functionalities• Sets of properties describing SDS resources:
• Tools and models• Data sources, data models• Decision process workflow templates• Case studies• Literature
Design considerations for SDS ontologies
Development process
• Literature review for a set of essential concepts and definitions
• Review of related web sites for user needs• Collaboration among domain experts (SDS Consortium
members) on critical issues:• What to include• Overall structure of ontology set (partition of concepts)• Discussion/debate/agreement on definitions of critical
concepts (two workshops; online discussions)• Review of the ontology implementation
• Iterative process of addition/review
Design considerations for SDS ontologies
Modular design
• 8 major components• 35 ontologies
Design considerations for SDS ontologies
Design considerations for SDS ontologies
Design considerations for SDS ontologies
Design considerations for SDS ontologies
Towards Developing an SDS Solution Portal
Design considerations for SDS ontologies
Choice and inclusion of classification schemes
E.g. Classification of methods and technique• Based on their functions serving spatial decision process steps• Based on whether they are for multi-objective or multi-attribute
decision making, whether they can handle uncertainty, etc.
E.g. Classification of SDS systems and tools• Based on their software type (system vs. tool)• Based on their the decision process steps they server• Based on their modeling application area (e.g. habitat suitability
modeling)
Design considerations for SDS ontologies
Choice and inclusion of classification schemes
The SDS ontologies can accommodate multiple classification schemes for the same group of concepts.
When a choice needs to be made, often it is driven by the need of the intended user community.
Design considerations for SDS ontologies
Degree of formalization
Concepts in SDS ontologies are defined by• Natural language description• Set of formally defined attributes
e.g. analysis-unit attribute of an SDS tool• Set of formally defined relations to other concepts
• Parent-child/sibling relations with other concepts• Other associative relations among concepts
e.g. method A is “implemented by” tools X and Y
Design considerations for SDS ontologiesA method used for this step – simple additive weighting
Simple additive weighting method
Abbreviation:SAW
Synonyms:weighted summation; boolean overlay; weighted linear combination method; WLC; scoring method
Definition:SAW is a multiattribute procedure based on the concept of a weighted average; it calculates a total score for each alternative by multiplying the importance weight assigned to each attribute by the scaled attribute value and summing the products over all attributes; the alternative with the highest overall score is best; the procedure can beperformed using GIS supporting overlay operations.
Source of description:Malczewski 1999, p.199
Decision typeDeterministic decision problem Individual decision making Multiattribute decision making
Decision Maker Interaction LevelModerateEditor...
input
• Attribute score • Criterion weight
• Ordinal rankingoutput
is a kind of
Multiattribute decision rule
used for Alternative ranking
imple
men
ted
by
• IDRISI• EMDS• ...
discussed in
...(publications)
Design considerations for SDS ontologiesEMDS – a tool implementing simple additive weighting
EMDS
EMDS
Name:Ecosystem Management Decision Support
Acronym:EMDS
Overview:The Ecosystem Management Decision Support (EMDS) system provides decision support for integrated landscape evaluation and planning. The system provides decision support for landscape-level analyses through logic and decision engines integrated with ArcGIS 8.1+. The logic engine evaluates landscape data against a formal logic specification, designed with NetWeaver Developer, to derive logic-based interpretations of ecosystem conditions such as biodiversity and sustainability. The decision engine evaluates NetWeaver outcomes (and data related to additional factors such as feasibility and efficacy of land management actions) against a decision model for prioritizing landscape features with decision models built in Criterium DecisionPlus
Platform:Windows XPCost:Free
...
used for decision process phase/steps
• Condition assessment• Choice• ...
methods implemented
• Multiattribute decision rule
• Uncertainty methods
accept data of process types
• Biophysical process• economic process• management process• Social process• ...
tool maker
• EMDS Consortium
analysis extent
• User specified
analysis unit
• User specified
software required
• ArcGIS 9.x• Crriterion Decision Plus• NetWeaver
used in case studies
• Sandy River Basin Anchor Habitat Project
• ...
Design considerations for SDS ontologies
Degree of formalization
• Use of inverse relations, for example,
• for decision process phases / steps and commonly used methods and techniques specify the reciprocal relations between a method and a process phase/step.
• methods and techniques implemented / implemented by tools specify the reciprocal relations between a tool and a method.
• used for decision process phases / steps and commonly used tools specify the reciprocal relations between a tool and a process phase/step
Design considerations for SDS ontologies
Degree of formalization
Dictated by the purpose of the ontologies
Set of attributes and relations that are minimal, but sufficient for the automation of information access as well as reasoning (to derive implicit knowledge)
Design considerations for SDS ontologies
Treatment of natural language
• Natural language term for concept• Abbreviations or acronyms• Synonyms• Description• Editorial notes (comments, editor, editor’s notes, etc.)
Design considerations for SDS ontologies
SDS Knowledge Repository
natural language term
abbreviation
synonyms
description
Design considerations for SDS ontologies
Modular design
• 800 concepts, and• 200 attributes and relations, partitioned into• 35 ontologies, grouped into• 8 major components
Design considerations for SDS ontologies
Component ContentIntroduction Definition of spatial decision support, the related fields of study, the
basic concepts related to the notion of decision
Decision context
The context in which to frame a decision: decision problem types, application domains, institutional, legal, social, cultural, geographic contexts of a decision
Spatial decision process
Knowledge about spatial decision processes: major phases and sub steps during a structured spatial decision process; typical spatial decision process workflows for different application domains
Methods and techniques
Methods and techniques used during a spatial decision process
Technology Technology available for SDS, including equipment and software, especially the spatial decision support systems and tools. Related information on information systems, general SDSS functionalities
People and participation
Collaborative dimension of decision making process, decision process participant roles
Domain data and knowledge
Data, data topics, data sources, data models, domain models
Resources SDS software systems and tools, domain models, related literature, case studies, related websites, data sources, data models, decision process workflow templates, organizations and people referred to elsewhere in the ontologies
Design considerations for SDS ontologies
Based on part of iso-19115.owl by Drexel University. Data topics re-implemented as classes instead of instances for future expansion for better topic granularity.
Potential interface with other ontologies
• “Upper level ontologies” potentially replaced by available better defined ontologies
Design considerations for SDS ontologies
Advantages of an ontology-based SDS Knowledge Portal
• Attributes and relations among concepts and formalized to facilitate automatic information retrieval
• Search query expansion based on multiple natural language references to the same concept
• Search query expansion based on parent-child relations• “Implicit knowledge” extraction based on relations that are
inverse, transitive, etc.• “Smart” recommendations based on semantic similarity among
concepts
Design considerations for SDS ontologies
Conclusion and future work
• SDS ontologies provide a conceptual framework for • Formally representing the body of knowledge in the field of SDS• Organizing various types SDS resources• Formally describing SDS resources for interoperability
• Future work• Improve the definition of concepts, especially in the area of
collaborative decision making• Include more representative, modular, reusable SDS resources,
especially tools and models• Consideration for different “dialect” among different user
communities (language and dialect tags on rdfs:label property of concepts)
Thank You
Design considerations for SDS ontologies
Karen Kemp, [email protected] Robert Raskin, [email protected] Naicong Li, [email protected]